Exposure to air pollution is associated with adverse health outcomes and people with pre- existing cardiovascular or respiratory disease are more susceptible. In particular, exposure to ozone is associated with exacerbations of asthma. There is also evidence from several studies that exposure to ozone is associated with the development of asthma, though these findings are not always consistent. Gene-environment interactions (GxE) have been proposed as an explanation for the inconsistency of the ozone -to-asthma association across studies. The investigators submit that by identifying these GxE in a mouse model of ozone-induced allergic airway disease (AAD) using an unbiased, genome-wide approach they can gain insight into the mechanisms by which ozone affects pulmonary and immune responses in the lung. To identify these GxE, the investigators will leverage a new mouse genetics resource, the Collaborative Cross (CC). The CC consists of a panel of recombinant inbred lines derived from eight-way crosses using a diverse set of inbred strains and provides ideal features for studying GxE and identifying the underlying molecular processes. Based on prior studies showing that ozone primes the immune system towards an allergy-prone phenotype, the investigators have designed a study in which mice are first exposed to ozone (or filtered air), and then are subjected to house dust mite (HDM) allergen sensitization and challenge (ozone-to-HDM) through the airway. In Aim 1, the investigators will characterize population level variation and heritability of AAD phenotypes in response to ozone-to-HDM among 100 CC lines. Based on this distribution, they will identify strains that have extreme responses (high and low) to ozone-to-HDM. These strains will be used in Aim 2 to test whether responses to ozone alone (neutrophilia and airway hyper-responsiveness) predict response to ozone-to-HDM and whether known effects of ozone on several immune parameters (macrophage, CD4+ T-cell, and dendritic cell number and activation status) are correlated with response to ozone-to-HDM. In Aim 3, the investigators will identify novel genetic and genomic predictors of response to ozone-to-HDM using genome- wide approaches. Specifically, they will measure lung gene expression using RNA-sequencing, and identify quantitative trait locus (QTL) and gene expression QTL (eQTL). Finally, by merging the QTL and eQTL data, the investigators will identify candidate genes for QTL using advanced statistical modeling and bioinformatic approaches. In summary, this grant application utilizes innovative and yet feasible approaches to identify genes and pathways that mediate the effect of ozone on subsequent response to allergen, and the results will offer new avenues of research into the health effects of ozone.